How much ad spend are you wasting?

Every ad platform marks its own homework. Meta says it drove the sale. Google says it drove the sale. TikTok says it drove the sale. They all take credit for the same purchase — and you pay all three of them for it.

This is called multi-touch attribution failure. When your customer sees a TikTok ad, Googles your brand, then clicks a Meta retargeting ad before buying, last-click attribution gives 100% credit to Meta. TikTok — which created the demand — gets zero.

The result? You cut TikTok spend (it "doesn't work"), Meta ROAS drops 3 weeks later (because the demand pipeline dried up), and you have no idea why. This cycle burns through 20-40% of your budget every single month.

Causal inference doesn't ask "who touched the customer last?" It asks "what would have happened without this channel?" That's the only question that matters for budget allocation.

Causality Engine uses Bayesian inference and Shapley values to fairly distribute credit across every touchpoint. The result is a confidence-scored view of each channel's true incremental contribution — so you can reallocate budget with certainty, not guesswork.